Paper Contents
Abstract
Integration of embedded wireless sensor networks in precision agriculture has impacted new, efficient, and well structured solutions for improving crop production. Typically, some of these sensors were integrated into the system to measure some parameters such as soil nutrients, humidity, temperature etc in real time and transmit data through wireless networks to the cloud. Wireless sensor networks (WSNs) face several challenges like coverage maintenance, improper node deployment, enabled wide connectivity, quality of service (QoS) provisions as well as resource allocation. To surmount these challenges, ant colony optimization (ACO) technique was applied in this study detect coverage holes caused as a result of improper node deployment. MATLAB and OPNET simulators were employed to simulate and evaluate the efficiency of the novel hole detection algorithm. The simulation result demonstrated an improvement in the system coverage performance when compared with other existing methods in terms of accuracy ratio, energy efficiency, reduction in resources demand and transmission range. Reduced number of ants were introduced through the virtual hole angles (VHAs) to accomplish efficient result. The result shows 10.1% reduction in the number of ants required to detect a hole in the network. As the number of holes increased, it was observed that the accuracy level of the developed algorithm increased. The performance evaluation also shows that more holes were discovered and efficiency ratio improved as the number of iterations increases. This result has effectively enhanced crop productivity with low energy consumption and in real time to ensure the sustainability of the sensor network.
Copyright
Copyright © 2024 Onuzulike Vincent Chukwuma. This is an open access article distributed under the Creative Commons Attribution License.
